Since VIS4AI techniques are widely used in both the data and model pipelines, this chapter provides a comprehensive overview of prevalent data types and machine learning models integral to these pipelines. We cover a range of data types, including tabular, sequential, multi-dimensional array, graph, and multi-modal data. On the model front, we explore various popular models categorized into classical models, deep learning models, and foundation models. In the category of classical models, we introduce linear/logistic regressions, decision trees and tree ensembles, and support vector machines (SVMs). Our investigation into deep learning models includes multi-layer perceptrons (MLPs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), graph neural networks (GNNs), deep generative models (DGMs), and transformers. Additionally, we explore advanced foundation models such as bidirectional encoder representations from transformers (BERT), vision transformer (ViT), InternImage, contrastive language-image pertaining (CLIP), and the generative pre-trained transformer (GPT) series models.